Objective The development of earlier and less invasive treatments for peripheral arterial disease requires a more complete understanding of vascular responses following a major arterial occlusion. A mechanistic model of the vasculature of the rat hindlimb is developed to predict acute (immediate) changes in vessel diameters and smooth muscle tone following femoral arterial occlusion. Methods Vascular responses of collateral arteries and distal arterioles to changes in pressure, shear stress, and metabolism are assessed before and after occlusion. The effects of exercise are also simulated and compared with venous flow measurements from WKY rats. Results The model identifies collateral arteries as the primary contributors to flow compensation following occlusion. Increasing the number of capillaries has minimal effect on blood flow while increasing the number of collateral arteries significantly increases flow, since the primary site of resistance shifts upstream to the collateral arteries following occlusion. Despite significant collateral dilation, calf flow remains below pre‐occlusion levels and the deficit becomes more severe with increased activity. Conclusions Although unable to compensate fully for an occlusion, the model demonstrates the importance of the shear response in collateral arteries and the metabolic response in the distal microcirculation in acute adaptations to a major arterial occlusion.
Objective There is currently a lack of clarity regarding which vascular segments contribute most significantly to flow compensation following a major arterial occlusion. This study uses hemodynamic principles and computational modeling to demonstrate the relative contributions of capillaries, arterioles, and collateral arteries at rest or exercise following an abrupt, total, and sustained femoral arterial occlusion. Methods The vascular network of the simulated rat hindlimb is based on robust measurements of blood flow and pressure in healthy rats from exercise and training studies. The sensitivity of calf blood flow to acute or chronic vascular adaptations in distinct vessel segments is assessed. Results The model demonstrates that decreasing the distal microcirculation resistance has almost no effect on flow compensation, while decreasing collateral arterial resistance is necessary to restore resting calf flow following occlusion. Full restoration of non‐occluded flow is predicted under resting conditions given all chronic adaptations, but only 75% of non‐occluded flow is restored under exercise conditions. Conclusion This computational method establishes the hemodynamic significance of acute and chronic adaptations in the microvasculature and collateral arteries under rest and exercise conditions. Regardless of the metabolic level being simulated, this study consistently shows the dominating significance of collateral vessels following an occlusion.
Genome-wide association studies (GWAS) have been extensively used to estimate the signed effects of trait-associated alleles. Recent independent studies failed to replicate the strong evidence of selection for height across Europe implying the shortcomings of standard population stratification correction approaches. Here, we present CluStrat, a stratification correction algorithm for complex population structure that leverages the linkage disequilibrium (LD)-induced distances between individuals. CluStrat performs agglomerative hierarchical clustering using the Mahalanobis distance and then applies sketching-based randomized ridge regression on the genotype data to obtain the association statistics. With the growing size of data, computing and storing the genome wide covariance matrix is a non-trivial task. We get around this overhead by computing the GRM directly using a connection between statistical leverage scores and the Mahalanobis distance. We test CluStrat on a large simulation study of discrete and admixed, arbitrarily-structured sub-populations identifying two to three-fold more true causal variants when compared to Principal Component (PC) based stratification correction methods while trading off for a slightly higher spurious associations. Applying CluStrat on WTCCC2 Parkinson's disease (PD) data, we identified loci mapped to a host of genes associated with PD such as BACH2, MAP2, NR4A2, SLC11A1, UNC5C to name a few. Availability and Implementation: CluStrat source code and user manual is available at: https://github.com/aritra90/CluStrat
BackgroundComplex disorders are caused by a combination of genetic, environmental and lifestyle factors, and their prevalence can vary greatly across different populations. Genome wide association studies (GWAS) can help identify common variants that underlie disease risk. However, despite their increasing number, the vast majority of studies focuses on European populations, leading to questions regarding the transferability of findings to non-Europeans. Here, we investigated whether polygenic risk scores (PRS) based on European GWAS correlate to disease prevalence within Europe and around the world.ResultsGWAS summary statistics of 20 different disorders were used to estimate PRS in nine European and 24 worldwide reference populations. We estimated the correlation between average genetic risk for each of the 20 disorders and their prevalence in Europe and around the world. A clear variation in genetic risk was observed based on ancestry and we identified populations that have a higher genetic liability for developing certain disorders both within European and global regions. We also found significant correlations between worldwide disease prevalence and PRS for 13 of the studied disorders with obesity genetic risk having the highest correlation to disease prevalence. For these 13 disorders we also found that the loci used in PRS are significantly more conserved across the different populations compared to randomly selected SNPs as revealed by Fst and linkage disequilibrium structure.ConclusionOur results show that PRS of world populations calculated based on European GWAS data can significantly capture differences in disease risk and identify populations with the highest genetic liability to develop various conditions. Our findings point to the potential transferability of European-based GWAS results to non-European populations and provide further support for the validity of GWAS.
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